Advancements in Cancer Imaging: Are Patients Reaping the Rewards?

Successful
cancer treatment relies heavily on timely and accurate diagnosis and continued
response assessment. The quality of the information provided by imaging
specialists and pathologists at diagnosis and beyond informs ongoing choices,
and ultimately the success or failure of treatment regimens. Traditional
techniques for tracking tumours, however, have been unable to keep pace with
the ever-growing number of increasingly sophisticated targeted agents and
immunotherapies. The recent explosion in novel cancer imaging techniques
should, therefore, provide much-needed support for oncologic care management.
However, a recent workshop hosted by the US National Cancer Policy Forum has
called into question whether these advancements are being optimally translated
into the clinic.

The importance
of accurate imaging is highlighted by higher mortality rates reported at
community hospitals compared to specialist cancer centres in the US. This is
posited to be due, in part, to the availability of subspecialty radiologists in
the latter, who have access to the insight of multidisciplinary cancer care
teams. Engagement of tumour boards to help integrate specialities, and
incentive schemes to encourage interdisciplinary collaboration have been
suggested by the aforementioned US forum. In the UK, the publication of
the Cancer Strategy 2015–2020 report1 outlined the
establishment and funding of Cancer Alliances across the country. This strategy
promised to bring together multidisciplinary teams across different hospital
trusts and, in particular, support the implementation of the new radiotherapy
service specification. The Royal College of Radiologists have since welcomed their
establishment, whilst highlighting the importance of communication with
patients and clinicians to ensure efficient and timely application of their
goals. The consensus appears to be that increased interdisciplinary
collaboration among specialities in cancer care is critical to improvement in
access to the latest imaging technologies and specialists.

Several
suggestions to changes in optimal practice models were suggested in the report
from the US National Cancer Policy Forum published in The Journal of Clinical
Oncology2; namely access to training for radiologists and therefore wider
access of oncology subspecialty radiologists to the public. Studies have
revealed a considerable rate of disagreement between second-opinion specialised
radiologists with initial cancer imaging reports. Even more worryingly, these
initial errors in imaging interpretations have resulted in the patient being
placed on inappropriate treatment regimes in up to 53.3% of cases2. The report
describes an insufficient total supply of such specialists to achieve
widespread geographic coverage in the United States and notes that oncologic
imaging is not even a formally recognised subspecialty in most countries.
Instead, radiology fellowships are usually based around a specific organ or
systems. The report, therefore, concludes that a concerted effort to improve
education and training in oncologic imaging is imperative. In the UK, the Royal
College of Radiologists has recommended a co-ordinated international
recruitment of radiology consultants in order to meet the ever-increasing
demand in scans; a 2017 report3 cited that
97% of NHS radiology departments failed to meet reporting requirements. As
discussed in the April 2019 editorial piece of this journal, the omnipresent
threat of Brexit on the NHS workforce threatens to hinder any progress made in
the cancer radiology division.

The employment
of structured and synoptic reporting, similar to that used in intensive care
and surgery, could facilitate a reduction in diagnostic errors and
unjustifiable geographic variations in cancer care. In the UK, the Royal
College of Radiologists has defined a comprehensive framework4 for the use
of machine learning and artificial intelligence (AI) within the NHS. It
highlights that the development of AI must be carried out at a rate and scale
appropriate to meet both the current workforce and patient demands. In the US,
software programmes which automate measurements of tumour volume and
segmentation to facilitate consistency in long term patient assessments are
available, but not yet broadly implemented in the clinic.

The role of
high-quality imaging in cancer care is continually growing with the emergence
of novel treatment strategies. The potential harm to patients caused by lack of
access to the latest cancer imaging techniques must be recognised and acted on.
In order to improve this gap in cancer care, efforts should be focused on three
main areas; development of multidisciplinary care teams which encourage
collaboration between oncology specialities, increased access to specialist
radiologists via concerted recruitment efforts and promotion of cancer imaging
training programmes, and the continued incorporation of innovative machine
learning and AI processes to streamline analysis and reporting of imaging data.

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